Spacetimes with Semantics (III) - The Structure of Functional Knowledge Representation and Artificial Reasoning
Using the previously developed concepts of semantic spacetime, I explore the
interpretation of knowledge representations, and their structure, as a semantic
system, within the framework of promise theory. By assigning interpretations to
phenomena, from observers to observed, we may approach a simple description of
knowledge-based functional systems, with direct practical utility. The focus is
especially on the interpretation of concepts, associative knowledge, and
context awareness. The inference seems to be that most if not all of these
concepts emerge from purely semantic spacetime properties, which opens the
possibility for a more generalized understanding of what constitutes a
learning, or even intelligent' system.
Some key principles emerge for effective knowledge representation: 1)
separation of spacetime scales, 2) the recurrence of four irreducible types of
association, by which intent propagates: aggregation, causation, cooperation,
and similarity, 3) the need for discrimination of identities (discrete), which
is assisted by distinguishing timeline simultaneity from sequential events, and
4) the ability to learn (memory). It is at least plausible that emergent
knowledge abstraction capabilities have their origin in basic spacetime
structures.
These notes present a unified view of mostly well-known results; they allow
us to see information models, knowledge representations, machine learning, and
semantic networking (transport and information base) in a common framework. The
notion of smart spaces' thus encompasses artificial systems as well as living
systems, across many different scales, e.g. smart cities and organizations.
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